scholarly journals Visibility Prediction over South Korea Based on Random Forest

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 552
Author(s):  
Bu-Yo Kim ◽  
Joo Wan Cha ◽  
Ki-Ho Chang ◽  
Chulkyu Lee
Keyword(s):  
Random Forest ◽  
South Korea ◽  
Correlation Coefficients ◽  
Predictive Performance ◽  
Air Pollutant ◽  
Economic Losses ◽  
Observation Data ◽  
Local Data ◽  
Weather Forecasts ◽  
Monitoring Service

In this study, the visibility of South Korea was predicted (VISRF) using a random forest (RF) model based on ground observation data from the Automated Synoptic Observing System (ASOS) and air pollutant data from the European Centre for Medium-Range Weather Forecasts (ECMWF) Copernicus Atmosphere Monitoring Service (CAMS) model. Visibility was predicted and evaluated using a training set for the period 2017–2018 and a test set for 2019. VISRF results were compared and analyzed using visibility data from the ASOS (VISASOS) and the Unified Model (UM) Local Data Assimilation and Prediction System (LDAPS) (VISLDAPS) operated by the Korea Meteorological Administration (KMA). Bias, root mean square error (RMSE), and correlation coefficients (R) for the VISASOS and VISLDAPS datasets were 3.67 km, 6.12 km, and 0.36, respectively, compared to 0.14 km, 2.84 km, and 0.81, respectively, for the VISASOS and VISRF datasets. Based on these comparisons, the applied RF model offers significantly better predictive performance and more accurate visibility data (VISRF) than the currently available VISLDAPS outputs. This modeling approach can be implemented by authorities to accurately estimate visibility and thereby reduce accidents, risks to public health, and economic losses, as well as inform on urban development policies and environmental regulations.

scholarly journals Next-Day Prediction of Hourly Solar Irradiance Using Local Weather Forecasts and LSTM Trained with Non-Local Data

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5258 ◽  
Author(s):  
Byung-ki Jeon ◽  
Eui-Jong Kim
Keyword(s):  
Solar Irradiance ◽  
Short Term Memory ◽  
Predictive Performance ◽  
Weather Forecast ◽  
Weather Data ◽  
Local Data ◽  
Weather Forecasts ◽  
Proposed Model ◽  
International Data ◽  
Limited Input Data

Solar irradiance prediction is significant for maximizing energy-saving effects in the predictive control of buildings. Several models for solar irradiance prediction have been developed; however, they require the collection of weather data over a long period in the predicted target region or evaluation of various weather data in real time. In this study, a long short-term memory algorithm–based model is proposed using limited input data and data from other regions. The proposed model can predict solar irradiance using next-day weather forecasts by the Korea Meteorological Administration and daily solar irradiance, and it is possible to build a model with one-time learning using national and international data. The model developed in this study showed excellent predictive performance with a coefficient of variation of the root mean square error of 12% per year even if the learning and forecast regions were different, assuming that the weather forecast was correct.

scholarly journals Application of Random Forest Algorithm for Merging Multiple Satellite Precipitation Products across South Korea

2021 ◽  
Vol 13 (20) ◽  
pp. 4033
Author(s):  
Giang V. Nguyen ◽  
Xuan-Hien Le ◽  
Linh Nguyen Van ◽  
Sungho Jung ◽  
Minho Yeon ◽  
...  
Keyword(s):  
Random Forest ◽  
South Korea ◽  
Learning Algorithm ◽  
Water Cycle ◽  
Spatiotemporal Variability ◽  
Observation System ◽  
Observation Data ◽  
Satellite Precipitation ◽  
Crucial Component ◽  
Grid Based

Precipitation is a crucial component of the water cycle and plays a key role in hydrological processes. Recently, satellite-based precipitation products (SPPs) have provided grid-based precipitation with spatiotemporal variability. However, SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution of these products is still relatively coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation based on a combination of rainfall observation data with multiple SPPs for the period of 2003–2017 across South Korea. A Random Forest (RF) machine-learning algorithm model was applied for producing a new merged precipitation product. In addition, several statistical linear merging methods have been adopted to compare with the results achieved from the RF model. To investigate the efficiency of RF, rainfall data from 64 observed Automated Synoptic Observation System (ASOS) installations were collected to analyze the accuracy of products through several continuous as well as categorical indicators. The new precipitation values produced by the merging procedure generally not only report higher accuracy than a single satellite rainfall product but also indicate that RF is more effective than the statistical merging method. Thus, the achievements from this study point out that the RF model might be applied for merging multiple satellite precipitation products, especially in sparse region areas.

scholarly journals Detection of Rhodococcus fascians, the Causative Agent of Lily Fasciation in South Korea

Pathogens ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 241
Author(s):  
Joon Moh Park ◽  
Jachoon Koo ◽  
Se Won Kang ◽  
Sung Hee Jo ◽  
Jeong Mee Park
Keyword(s):  
Phylogenetic Analysis ◽  
South Korea ◽  
Nicotiana Benthamiana ◽  
Economic Value ◽  
Virulence Gene ◽  
Economic Losses ◽  
Herbaceous Perennials ◽  
Rhodococcus Fascians ◽  
Different Strains

Rhodococcus fascians is an important pathogen that infects various herbaceous perennials and reduces their economic value. In this study, we examined R. fascians isolates carrying a virulence gene from symptomatic lily plants grown in South Korea. Phylogenetic analysis using the nucleotide sequences of 16S rRNA, vicA, and fasD led to the classification of the isolates into four different strains of R. fascians. Inoculation of Nicotiana benthamiana with these isolates slowed root growth and resulted in symptoms of leafy gall. These findings elucidate the diversification of domestic pathogenic R. fascians and may lead to an accurate causal diagnosis to help reduce economic losses in the bulb market.

scholarly journals The First National Survey of Cadmium in Cacao Farm Soil in Colombia

Agronomy ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 761
Author(s):  
Daniel Bravo ◽  
Clara Leon-Moreno ◽  
Carlos Alberto Martínez ◽  
Viviana Marcela Varón-Ramírez ◽  
Gustavo Alfonso Araujo-Carrillo ◽  
...  
Keyword(s):  
Graphical Models ◽  
Partial Correlation ◽  
National Level ◽  
Prediction Method ◽  
Correlation Coefficients ◽  
Predictive Performance ◽  
Nationwide Survey ◽  
Critical Discussion ◽  
Cadmium Content ◽  
Soil Variables

This study represents the first nationwide survey regarding the distribution of Cd content in cacao-growing soils in Colombia. The soil Cd distribution was analyzed using a cold/hotspots model. Moreover, both descriptive and predictive analytical tools were used to assess the key factors regulating the Cd concentration, considering Cd content and eight soil variables in the cacao systems. A critical discussion was performed in four main cacao-growing districts. Our results suggest that the performance of a model using all the variables will always be superior to the one using Zn alone. The analyzed variables featured an appropriate predictive performance, nonetheless, that performance has to be improved to develop a prediction method that might be used nationwide. Results from the fitted graphical models showed that the largest associations (as measured by the partial correlation coefficients) were those between Cd and Zn. Ca had the second-largest partial correlation with Cd and its predictive performance ranked second. Interestingly, it was found that there was a high variability in the factors correlated with Cd in cacao growing soils at a national level. Therefore, this study constitutes a baseline for the forthcoming studies in the country and should be reinforced with an analysis of cadmium content in cacao beans.

scholarly journals Genetic Characteristics of Avian Influenza Virus Isolated from Wild Birds in South Korea, 2019–2020

Viruses ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 381
Author(s):  
Eun-Jee Na ◽  
Young-Sik Kim ◽  
Sook-Young Lee ◽  
Yoon-Ji Kim ◽  
Jun-Soo Park ◽  
...  
Keyword(s):  
Avian Influenza ◽  
South Korea ◽  
Basic Amino Acid ◽  
Histopathological Change ◽  
Amino Acid Sequences ◽  
Wild Birds ◽  
Influenza Viruses ◽  
Economic Losses ◽  
Active Monitoring ◽  
Genetic Characteristics

Wild aquatic birds, a natural reservoir of avian influenza viruses (AIVs), transmit AIVs to poultry farms, causing huge economic losses. Therefore, the prevalence and genetic characteristics of AIVs isolated from wild birds in South Korea from October 2019 to March 2020 were investigated and analyzed. Fresh avian fecal samples (3256) were collected by active monitoring of 11 wild bird habitats. Twenty-eight AIVs were isolated. Seven HA and eight NA subtypes were identified. All AIV hosts were Anseriformes species. The HA cleavage site of 20 representative AIVs was encoded by non-multi-basic amino acid sequences. Phylogenetic analysis of the eight segment genes of the AIVs showed that most genes clustered within the Eurasian lineage. However, the HA gene of H10 viruses and NS gene of four viruses clustered within the American lineage, indicating intercontinental reassortment of AIVs. Representative viruses likely to infect mammals were selected and evaluated for pathogenicity in mice. JB21-58 (H5N3), JB42-93 (H9N2), and JB32-81 (H11N2) were isolated from the lungs, but JB31-69 (H11N9) was not isolated from the lungs until the end of the experiment at 14 dpi. None of infected mice showed clinical sign and histopathological change in the lung. In addition, viral antigens were not detected in lungs of all mice at 14 dpi. These data suggest that LPAIVs derived from wild birds are unlikely to be transmitted to mammals. However, because LPAIVs can reportedly infect mammals, including humans, continuous surveillance and monitoring of AIVs are necessary, despite their low pathogenicity.

scholarly journals Evaluation of the Variability of the ORF34, ORF68, and MLST Genes in EHV-1 from South Korea

Pathogens ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 425
Author(s):  
Hyung-Woo Kang ◽  
Eun-Yong Lee ◽  
Kyoung-Ki Lee ◽  
Mi-Kyeong Ko ◽  
Ji-Young Park ◽  
...  
Keyword(s):  
Nucleotide Sequence ◽  
South Korea ◽  
Molecular Level ◽  
Economic Losses ◽  
Equine Herpesvirus ◽  
Equine Herpesvirus 1 ◽  
Mlst Analysis ◽  
Herpesvirus 1 ◽  
First Time ◽  
Group 1

Equine herpesvirus-1 (EHV-1) is an important pathogen in horses. It affects horses worldwide and causes substantial economic losses. In this study, for the first time, we characterized EHV-1 isolates from South Korea at the molecular level. We then aimed to determine the genetic divergences of these isolates by comparing them to sequences in databases. In total, 338 horse samples were collected, and 12 EHV-1 were isolated. We performed ORF30, ORF33, ORF68, and ORF34 genetic analysis and carried out multi-locus sequence typing (MLST) of 12 isolated EHV-1. All isolated viruses were confirmed as non-neuropathogenic type, showing N752 of ORF30 and highly conserved ORF33 (99.7–100%). Isolates were unclassified using ORF68 analysis because of a 118 bp deletion in nucleotide sequence 701–818. Seven EHV-1 isolates (16Q4, 19R166-1, 19R166-6, 19/10/15-2, 19/10/15-4, 19/10/18-2, 19/10/22-1) belonged to group 1, clade 10, based on ORF34 and MLST analysis. The remaining 5 EHV-1 isolates (15Q25-1, 15D59, 16Q5, 16Q40, 18D99) belonged to group 7, clade 6, based on ORF34 and MLST analysis.

scholarly journals Characteristics of Stratospheric Winds over Jiuquan (41.1°N, 100.2°E) Using Rocketsonde Data in 1967–2004

2017 ◽  
Vol 34 (3) ◽  
pp. 657-667 ◽  
Author(s):  
Z. Sheng ◽  
J. W. Li ◽  
Y. Jiang ◽  
S. D. Zhou ◽  
W. L. Shi
Keyword(s):  
Zonal Wind ◽  
Middle Atmosphere ◽  
Correlation Coefficients ◽  
Meridional Wind ◽  
Horizontal Wind ◽  
Cycle Period ◽  
Observation Data ◽  
Wind Fields ◽  
Zonal Winds ◽  
Model Research

AbstractStratospheric winds play a significant role in middle atmosphere dynamics, model research, and carrier rocket experiments. For the first time, 65 sets of rocket sounding experiments conducted at Jiuquan (41.1°N, 100.2°E), China, from 1967 to 2004 are presented to study horizontal wind fields in the stratosphere. At a fixed height, wind speed obeys the lognormal distribution. Seasonal mean winds are westerly in winter and easterly in summer. In spring and autumn, zonal wind directions change from the upper to the lower stratosphere. The monthly zonal mean winds have an annual cycle period with large amplitudes at high altitudes. The correlation coefficients for zonal winds between observations and the Horizontal Wind Model (HWM) with all datasets are 0.7. The MERRA reanalysis is in good agreement with rocketsonde data according to the zonal winds comparison with a coefficient of 0.98. The sudden stratospheric warming is an important contribution to biases in the HWM, because it changes the zonal wind direction in the midlatitudes. Both the model and the reanalysis show dramatic meridional wind differences with the observation data.

Aerosol Assimilation of lidar data from Satellite (AEOLUS) and Ground-based (EARLINET) instruments in COMPO-IFS.

2021 ◽  
Author(s):  
Julie Letertre-Danczak ◽  
Angela Benedetti ◽  
Drasko Vasiljevic ◽  
Alain Dabas ◽  
Thomas Flament ◽  
...  
Keyword(s):  
Quality Data ◽  
Lidar Data ◽  
Operational Model ◽  
Weather Forecasts ◽  
The Past ◽  
Medium Range ◽  
First Results ◽  
Monitoring Service ◽  
The Vertical Distribution ◽  
Good Quality Data

<p>Since several years, the number of aerosol data coming from lidar has grown and improved in quality. These new datasets are providing a valuable information on the vertical distribution of aerosols which is missing in the AOD (Aerosol Optical Depth), which has been used so far in aerosols analysis. The launch of AEOLUS in 2018 has increased the interest in the assimilation of the aerosol lidar information. In parallel, the ground-based network EARLINET (European Aerosol Research LIdar NETwork) has grown to cover the Europe with good quality data. Assimilation of these data in the ECMWF/CAMS (European Centre for Medium-range Weather Forecasts / Copernicus Atmosphere Monitoring Service) system is expected to provide improvements in the aerosol analyses and forecasts.<br><br>Three preliminary studies have been done in the past four years using AEOLUS data (A3S-ESA funded) and EARLINET data (ACTRIS-2 and EUNADIC-AV, EU-funded). These studies have allowed the full development of the tangent linear and adjoint code for lidar backscatter in the ECMWF's 4D-VAR system. These developments are now in the operational model version in research mode. The first results are promising and open the path to more intake of aerosol lidar data for assimilation purposes. The future launch of EARTHCARE (Earth-Cloud Aerosol and Radiation Explorer) and later ACCP (Aerosol Cloud, Convention and Precipitation) might even upgrade the use of aerosol lidar data in COMPO-IFS (Composition-Integrated Forecast system).<br><br>The most recent results using AEOLUS data (for October 2019 and April 2020) and using EARLINET data (October 2020) will be shown in this presentation. The output will be compared to the CAMS operational aerosol forecast as well as to independent data from AERONET (AErosol Robotic NETwork).</p>

scholarly journals GIST-PM-Asia v1: development of a numerical system to improve particulate matter forecasts in South Korea using geostationary satellite-retrieved aerosol optical data over Northeast Asia

2016 ◽  
Vol 9 (1) ◽  
pp. 17-39 ◽  
Author(s):  
S. Lee ◽  
C. H. Song ◽  
R. S. Park ◽  
M. E. Park ◽  
K. M. Han ◽  
...  
Keyword(s):  
Particulate Matter ◽  
South Korea ◽  
Northeast Asia ◽  
Initial Distribution ◽  
Low Earth Orbit ◽  
Optical Data ◽  
Future Research ◽  
Observation Data ◽  
Forecast System ◽  
Short Term

Abstract. To improve short-term particulate matter (PM) forecasts in South Korea, the initial distribution of PM composition, particularly over the upwind regions, is primarily important. To prepare the initial PM composition, the aerosol optical depth (AOD) data retrieved from a geostationary equatorial orbit (GEO) satellite sensor, GOCI (Geostationary Ocean Color Imager) which covers a part of Northeast Asia (113–146° E; 25–47° N), were used. Although GOCI can provide a higher number of AOD data in a semicontinuous manner than low Earth orbit (LEO) satellite sensors, it still has a serious limitation in that the AOD data are not available at cloud pixels and over high-reflectance areas, such as desert and snow-covered regions. To overcome this limitation, a spatiotemporal-kriging (STK) method was used to better prepare the initial AOD distributions that were converted into the PM composition over Northeast Asia. One of the largest advantages in using the STK method in this study is that more observed AOD data can be used to prepare the best initial AOD fields compared with other methods that use single frame of observation data around the time of initialization. It is demonstrated in this study that the short-term PM forecast system developed with the application of the STK method can greatly improve PM10 predictions in the Seoul metropolitan area (SMA) when evaluated with ground-based observations. For example, errors and biases of PM10 predictions decreased by  ∼  60 and  ∼  70 %, respectively, during the first 6 h of short-term PM forecasting, compared with those without the initial PM composition. In addition, the influences of several factors on the performances of the short-term PM forecast were explored in this study. The influences of the choices of the control variables on the PM chemical composition were also investigated with the composition data measured via PILS-IC (particle-into-liquid sampler coupled with ion chromatography) and low air-volume sample instruments at a site near Seoul. To improve the overall performances of the short-term PM forecast system, several future research directions were also discussed and suggested.

scholarly journals Accurate mobile remote sensing of XCO<sub>2</sub> and XCH<sub>4</sub> latitudinal transects from aboard a research vessel

2015 ◽  
Vol 8 (12) ◽  
pp. 5023-5038 ◽  
Author(s):  
F. Klappenbach ◽  
M. Bertleff ◽  
J. Kostinek ◽  
F. Hase ◽  
T. Blumenstock ◽  
...  
Keyword(s):  
Absorption Spectrometry ◽  
Total Carbon ◽  
Research Vessel ◽  
Weather Forecasts ◽  
Technical Developments ◽  
Solar Tracker ◽  
Network Instrument ◽  
Monitoring Service ◽  
Gosat Satellite ◽  
Better Than

Abstract. A portable Fourier transform spectrometer (FTS), model EM27/SUN, was deployed onboard the research vessel Polarstern to measure the column-average dry air mole fractions of carbon dioxide (XCO2) and methane (XCH4) by means of direct sunlight absorption spectrometry. We report on technical developments as well as data calibration and reduction measures required to achieve the targeted accuracy of fractions of a percent in retrieved XCO2 and XCH4 while operating the instrument under field conditions onboard the moving platform during a 6-week cruise on the Atlantic from Cape Town (South Africa, 34° S, 18° E; 5 March 2014) to Bremerhaven (Germany, 54° N, 19° E; 14 April 2014). We demonstrate that our solar tracker typically achieved a tracking precision of better than 0.05° toward the center of the sun throughout the ship cruise which facilitates accurate XCO2 and XCH4 retrievals even under harsh ambient wind conditions. We define several quality filters that screen spectra, e.g., when the field of view was partially obstructed by ship structures or when the lines-of-sight crossed the ship exhaust plume. The measurements in clean oceanic air, can be used to characterize a spurious air-mass dependency. After the campaign, deployment of the spectrometer alongside the TCCON (Total Carbon Column Observing Network) instrument at Karlsruhe, Germany, allowed for determining a calibration factor that makes the entire campaign record traceable to World Meteorological Organization (WMO) standards. Comparisons to observations of the GOSAT satellite and concentration fields modeled by the European Centre for Medium-Range Weather Forecasts (ECMWF) Copernicus Atmosphere Monitoring Service (CAMS) demonstrate that the observational setup is well suited to provide validation opportunities above the ocean and along interhemispheric transects.

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